Publication:
Generalized order acceptance and scheduling problem with batch delivery: models and metaheuristics

dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorOğuz, Ceyda
dc.contributor.kuauthorTarhan, İstenç
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-10T00:07:48Z
dc.date.issued2021
dc.description.abstractThis paper addresses an extended version of the generalized order acceptance and scheduling problem by including the logistics aspects into the production scheduling decisions. While order acceptance and scheduling feature of the problem includes the joint decision of which orders to accept and how to schedule them due to the limited capacity in production environment and due to the order delivery time requirements for the customers, logistics aspect of the problem entails the decision of how to batch the accepted orders for the delivery in conjunction with the production scheduling. The objective is to maximize the net revenue in line with the literature of order acceptance and scheduling problem. We first present a mixed integer linear programming and a constraint programming model for this problem. To tackle large size problem instances in which these models fail, we propose an iterated local search algorithm using a new local search scheme. To evaluate the performance of the proposed local search scheme, a variant of this algorithm is developed which replaces the relevant scheme with tabu search. Computational results show that the proposed models achieve small optimality gaps for the small size problems, but their performances deteriorate significantly as the problem size enlarges. For the large size problem instances, the iterated local search algorithm using the proposed local search scheme achieves smaller optimality gaps compared to the one with the tabu search algorithm.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume134
dc.identifier.doi10.1016/j.cor.2021.105414
dc.identifier.eissn1873-765X
dc.identifier.issn0305-0548
dc.identifier.scopus2-s2.0-85107941475
dc.identifier.urihttps://doi.org/10.1016/j.cor.2021.105414
dc.identifier.urihttps://hdl.handle.net/20.500.14288/16848
dc.identifier.wos672702000021
dc.keywordsScheduling
dc.keywordsOrder acceptance
dc.keywordsBatch delivery
dc.keywordsLocal search
dc.keywordsMathematical models
dc.keywordsMetaheuristics
dc.keywordsBound algorithm
dc.keywordsLocal search
dc.keywordsTabu search
dc.keywordsTardiness
dc.keywordsEarliness
dc.keywordsShop
dc.keywordsJobs
dc.language.isoeng
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofComputers and Operations Research
dc.subjectComputer Science
dc.subjectArtificial intelligence
dc.subjectIndustrial engineering
dc.subjectOperations research
dc.subjectManagement science
dc.titleGeneralized order acceptance and scheduling problem with batch delivery: models and metaheuristics
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorTarhan, İstenç
local.contributor.kuauthorOğuz, Ceyda
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Industrial Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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